Most genetic variants associated with complex heritability phenotypes lie in non-coding regions and are thought to influence disease risk by regulating gene expression. However, most transcriptome-wide association approaches primarily model local (cis) genetic effects, leaving much of gene regulation unexplained. Here, we show that incorporating distal (trans) regulatory effects improves the prediction of gene expression and the identification of disease-associated genes. Using RNA sequencing data from six human post-mortem brain regions, we developed INGENE and MODULE, two models capturing the combined influence of candidate trans-acting variants within gene coexpression networks. Integrating these models with conventional cis-based predictors improved gene expression imputation (maximum likelihood estimation, α = 0.05) for 18,744 genes across regions. Applying this framework to Psychiatric Genomics Consortium wave 3 genotypes identified 766 genes associated with schizophrenia (PFDR < 0.01), including 641 not previously reported by transcriptome-wide analyses. These findings highlight the contribution of distal regulatory mechanisms and gene network interactions to schizophrenia risk.

Non-coding genetic variants statistically associated with complex heritability phenotypes are thought to act primarily through transcriptome regulatory mechanisms. Predictions of gene expression in tissue like the human brain traditionally rely primarily on cis -eQTLs. Here, we introduce INGENE and MODULE, trans -eQTLs models designed to enhance the prediction of gene expression by capturing the collective impact of candidate trans -eQTLs acting within co-expression networks. Exploiting RNA-seq data in six post-mortem brain regions (amygdala, caudate nucleus, dorsal/subgenual anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus), we validate our models on two testing datasets, demonstrating increased gene predictability compared to both an original cis -based model and to EpiXcan, the leading benchmark in cis -model performance. Integration of cis - and trans -predictions significantly improves gene-level expression imputation (MLE α= 0.05) for 18,744 genes across the six brain regions considered. Applying cis and trans models to PGC wave 3 genotypes identifies 766 SCZ-associated genes across brain regions (pFDR < .01), emphasizing the complementary nature of cis and trans predictions in trait association discovery. Of these genes, 641 represent novel transcriptome-wide associations with schizophrenia, highlighting the role of trans -heritability and genetic interactions underlying risk for this disorder, in addition to further supporting 125 previous candidates. ### Competing Interest Statement A. Bertolino received consulting fees from Biogen and lecture fees from Otsuka, Janssen, and Lundbeck. D. Weinberger serves on the scientific advisory boards of Sage Therapeutics and Pasithea Therapeutics. G. Pergola and G. C. Kikidis received lecture fees from Lundbeck. A. K. Malhotra is a consultant to Genomind, InformedDNA and Concert Pharmaceuticals. M. C. O Donovan, M. J. Owen, and J. T. R. Walters are supported by collaborative research grants from Takeda Pharmaceuticals. O. A. Andreassen is a consultant for HealthLytix and received speaker s honoraria from Lundbeck. C. Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Minerva, Otsuka, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. Research Projects of National Relevance 2020 (PRIN 2020; 2020WSCSLZ) Research Projects of National Relevance 2022 (PRIN 2022; 2022KXJYJA) Research Projects Of National Relevance PNRR 2022 (P2022HNBJX) The LIBD funded the collection and analysis of postmortem brain tissue

Antipsychotic medications are the first-line treatment for schizophrenia. Around 40

Rare copy number variants (CNVs) are a key component of the genetic basis of psychiatric conditions, but have not been well characterized for most. We conducted a genome-wide CNV analysis across six diagnostic categories (N = 574,965): autism (ASD), ADHD, bipolar disorder (BD), major depressive disorder (MDD), PTSD, and schizophrenia (SCZ). We identified 35 genome-wide significant associations at 18 loci, including novel associations in SCZ ( SMYD3, USP7 - HAPSTR1 ) and in the combined cross-disorder analysis ( ASTN2 ). Rare CNVs accounted for 1-3% of heritability across diagnoses. In ASD, associations were uniformly positive, consistent with autism having diverse etiologies and clinical presentations. By contrast, CNVs showed a dose-dependent relationship for other diagnoses, including SCZ and PTSD, with reciprocal deletions and duplications having inversely correlated effects and distinct genotype-phenotype relationships. Our findings suggest that genes have effects that are both dose-dependent and pleiotropic, such that a positive influence on one dimension of psychopathology may be accompanied by positive or negative effects on others.

Background and Hypothesis: Antipsychotic medications are the first-line treatment for schizophrenia. However, around 40% of people with schizophrenia who are treated with antipsychotics could develop extrapyramidal side-effects (EPSE) including: 1) Dyskinesias, 2) Parkinsonism, 3) Akathisia, and 4) Dystonia. Study Design: We conducted Genome-wide association (GWAS) and Epigenome-wide association (EWAS) meta-analysis of EPSE utilising data from previous schizophrenia case control studies. We integrated significant EWAS findings to an EPSE GWAS meta-analysis to enhance our understanding of the functional impact of common variants on EPSE. We also investigated whether polygenic risk scores (PRS) for schizophrenia, Parkinson's disease, and Lewy-body dementia could be predictive of EPSE development. Study Results: The top index SNP rs2709733 (A/G) from EPSE GWAS (p=2.214x10-7) mapped to a long intergenic non-protein coding RNA, LINC01162 with consistent effects across all cohorts. We identified 9 differentially methylated positions (DMPs) associated with EPSE when controlling for methylation age, sex, derived estimates of cell composition, smoking score, and schizophrenia PRS. Four of the DMPs cg14531564, cg20647656, cg12004641, cg22845912, and their affiliated genes (SDF4, ANKMY1, TNS1, SLA) were associated with the risk of developing EPSE and not with schizophrenia risk. Another DMP (cg12044923) which mapped to the STK32B gene, showed significant enrichment for association with risk of EPSE. Conclusions: Our study sheds new light on the potential biological mechanisms underlying EPSE development in schizophrenia, highlighting the importance of exploring both methylation shifts and common SNP associations. Further research with larger samples sizes and a focus on the role of STK32B are encouraged. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement UCL participant recruitment was also funded by the Medical Research Council (MRC grant code G1000708). The Cardiff participants were recruited by the CardiffCOGS project, supported by a Medical Research Council Programme Grant (MR/Y004094/1) and The National Centre for Mental Health (funded by the Welsh Government through Health and Care Research Wales). AM and NB were supported by the UCLH NIHR BRC. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the NHS Metropolitan Multi-centre Research Ethics Committee (MREC/03/11/090). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

The brain neurotramsmitter dopamine may play an important role in modulating systemic glucose homeostasis. In seven hundred and four drug- naïve patients with first-episode schizophrenia, we provide robust evidence of positive associations between negative symptoms of schizophrenia and high fasting blood glucose. We then show that glucose metabolism and negative symptoms are improved when intermittent theta burst stimulation (iTBS) on prefrontal cortex (PFC) is performed in patients with predominantly negative symptoms of schizophrenia. These findings led us to hypothesize that the prefrontal cortical dopamine deficit, which is known to be associated with negative symptoms, may be responsible for abnormal glucose metabolism in schizophrenia. To explore this, we optogenetically and chemogenetically inhibited the ventral tegmental area (VTA)-medial prefrontal cortex (mPFC) dopamine projection in mice and found both procedures caused glucose intolerance. Moreover, microinjection of dopamine two receptor (D2R) neuron antagonists into mPFC in mice significantly impaired glucose tolerance. Finally, a transgenic mouse model of psychosis named Disc1tr exhibited depressive-like symptoms, impaired glucose homeostasis, and compared to wild type littermates reduced D2R expression in prefrontal cortex.

Previous studies have demonstrated that the levels of IgG against neurotransmitter receptors are increased in patients with schizophrenia. Genome-wide association (GWA) studies of schizophrenia confirmed that 108 loci harbouring over 300 genes were associated with schizophrenia. Although the functional implications of genetic variants are unclear, theoretical functional alterations of these genes could be replicated by the presence of autoantibodies. This study examined the levels of plasma IgG antibodies against four neurotransmitter receptors, CHRM4, GRM3, CHRNA4 and CHRNA5, using an in-house ELISA in 247 patients with schizophrenia and 344 non-psychiatric controls. Four peptides were designed based on in silico analysis with computational prediction of HLA-DRB1 restricted and B-cell epitopes. The relationship between plasma IgG levels and psychiatric symptoms, as defined by the Operational Criteria Checklist for Psychotic Illness and Affective Illness (OPCRIT), were examined. The results showed that the levels of plasma IgG against peptides derived from CHRM4 and CHRNA4 were significantly increased in patients with schizophrenia compared with control subjects, but there was no significant association of plasma IgG levels with any symptom domain or any specific symptoms. These preliminary results suggest that CHRM4 and CHRNA4 may be novel targets for autoantibody responses in schizophrenia, although the pathogenic relationship between increased serum autoantibody levels and schizophrenia symptoms remains unclear.

Abstract Background The study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex. Results We found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02–5.61, P = 1.1E−03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status. Conclusions Our study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

Autoantibodies targeting the central nervous system have been shown to induce psychiatric symptoms resembling schizophrenia. Concurrently, genetic studies have characterised a number of risk variants associated with schizophrenia although their functional implications are largely unknown. Any biological effects of functional variants on protein function may potentially be replicated by the presence of autoantibodies against such proteins. Recent research has demonstrated that the R1346H variant in the CACNA1I gene coding for the Cav 3.3 protein results in a synaptic reduction of Cav3.3 voltage gated calcium channels and, consequently, sleep spindles, which have been shown to correlate with several symptom domains in patients with schizophrenia. The present study measured plasma levels of IgG against two peptides derived from CACNA1I and CACNA1C, respectively, in patients with schizophrenia and healthy controls. The results demonstrated that increased anti-CACNA1I IgG levels were associated with schizophrenia but not associated with any symptom domain related to the reduction of sleep spindles. In contrast to previously published work indicating that inflammation may be a marker for a depressive phenotype, plasma levels of IgG against either CACNA1I or CACNA1C peptides were not associated with depressive symptoms, suggesting that anti-Cav3.3 autoantibodies may function independently of pro-inflammatory processes.

Background This study attempts to replicate in a Chinese population an earlier UK report that eye movement abnormalities can accurately distinguish schizophrenia (SCZ) cases from healthy controls (HCs). It also seeks to determine whether first-episode SCZ differ from chronic SCZ and whether these eye movement abnormalities are enriched in psychosis risk syndrome (PRS). Methods The training set included 104 Chinese HC and 60 Chinese patients with SCZ, and the testing set included 20 SCZ patients and 20 HC from a UK cohort. An additional 16 individuals with PRS were also enrolled. Eye movements of all participants were recorded during free-viewing, smooth pursuit, and fixation stability tasks. Group differences in 55 performance measures were compared and a gradient-boosted decision tree model was built for predictive analyses. Results Extensive eye-movement abnormalities were observed in patients with SCZ on almost all eye-movement tests. On almost all individual variables, first-episode patients showed no statistically significant differences compared with chronic patients. The classification model was able to discriminate patients from controls with an area under the curve of 0.87; the model also classified 88% of PRS individuals as SCZ-like. Conclusions Our findings replicate and extend the UK results. The overall accuracy of the Chinese study is virtually identical to the UK findings. We conclude that eye-movement abnormalities appear early in the natural history of the disorder and can be considered as potential trait markers for SCZ diathesis.

The characteristic maximum lifespan varies enormously across animal species from a few hours to hundreds of years. This argues that maximum lifespan, and the ageing process that itself dictates lifespan, are to a large extent genetically determined. Although controversial, this is supported by firm evidence that semelparous species display evolutionarily programmed ageing in response to reproductive and environmental cues. Parabiosis experiments reveal that ageing is orchestrated systemically through the circulation, accompanied by programmed changes in hormone levels across a lifetime. This implies that, like the circadian and circannual clocks, there is a master 'clock of age' (circavital clock) located in the limbic brain of mammals that modulates systemic changes in growth factor and hormone secretion over the lifespan, as well as systemic alterations in gene expression as revealed by genomic methylation analysis. Studies on accelerated ageing in mice, as well as human longevity genes, converge on evolutionarily conserved fibroblast growth factors (FGFs) and their receptors, including KLOTHO, as well as insulin-like growth factors (IGFs) and steroid hormones, as key players mediating the systemic effects of ageing. Age-related changes in these and multiple other factors are inferred to cause a progressive decline in tissue maintenance through failure of stem cell replenishment. This most severely affects the immune system, which requires constant renewal from bone marrow stem cells. Age-related immune decline increases risk of infection whereas lifespan can be extended in germfree animals. This and other evidence suggests that infection is the major cause of death in higher organisms. Immune decline is also associated with age-related diseases. Taking the example of Alzheimer's disease (AD), we assess the evidence that AD is caused by immunosenescence and infection. The signature protein of AD brain, Aβ, is now known to be an antimicrobial peptide, and Aβ deposits in AD brain may be a response to infection rather than a cause of disease. Because some cognitively normal elderly individuals show extensive neuropathology, we argue that the location of the pathology is crucial - specifically, lesions to limbic brain are likely to accentuate immunosenescence, and could thus underlie a vicious cycle of accelerated immune decline and microbial proliferation that culminates in AD. This general model may extend to other age-related diseases, and we propose a general paradigm of organismal senescence in which declining stem cell proliferation leads to programmed immunosenescence and mortality.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

Purpose Women diagnosed with non-affective psychosis have a lower general fertility rate (GFR) and age-specific fertility rate (ASFR) than women in the general population. Contemporary data on GFR in this group remain limited, despite substantive changes in prescribing and management. We calculated contemporary estimates of the GFR and ASFR for women diagnosed with non-affective psychosis compared with the general population of women without this diagnosis. Methods A population-based design combined routinely collected historical maternity and psychiatric data from two representative areas of Scotland. Women were included from the NHS Grampian or Greater Glasgow and Clyde areas and were aged 15–44 between 2005 and 2013 inclusive. The ‘exposed’ group had a diagnosis of non-affective psychosis (ICD-10 F20–F29) and was compared to the general population of 'unexposed' women in the same geographical areas. Results Annual GFR between 2005 and 2013 for women with non-affective psychosis varied from 9.6 to 21.3 live births/1000 women per year in the exposed cohort and 52.7 to 57.8 live births/1000 women per year in the unexposed cohort, a rate ratio (RR) of 0.28 [ p < 0.001; 95% CI (0.24, 0.32)]. ASFR for all 5-year age groups was lower in the exposed cohort than amongst unexposed women. Conclusion We highlight continued low fertility rates in women with a diagnosis of non-affective psychosis, despite widespread availability of prolactin-sparing atypical antipsychotics. Accurate estimation of fertility rates remains crucial in developing needs-matched perinatal care for these women. Methodological improvements using routine datasets to investigate perinatal mental health are also urgently needed.

IMPORTANCE About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. OBJECTIVE To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. DESIGN, SETTING, AND PARTICIPANTS Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). MAIN OUTCOMES AND MEASURES GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. RESULTS The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r(2) = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r(2) = 1.09%; P = .04). CONCLUSIONS AND RELEVANCE In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.

OBJECTIVE:To find eye movement characteristics in patients with affective disorders. METHOD:The demographic and clinical evaluation data of patients with major depressive disorder (MDD), bipolar disorder (BPD), and healthy control (HC) were collected. EyeLink 1000 eye tracker was used to collect eye movement data. Chi-squared test and independent sample t-test were used for demographics and clinical characteristics. The Mann-Whitney U-test was used to compare the eye movement variables among four groups, and the FDR method was used for multiple comparison correction. Pearson correlation analysis was used to analyse the relationship between clinical symptoms and eye movement variables. RESULTS:Patients with affective disorders showed smaller saccade amplitude under free-viewing task, more fixations and saccades, shorter fixation duration, longer saccade duration under fixation stability and smooth pursuit tasks (all, p < 0.05) when compared to HC, but there was no significant difference in all eye movement variables among patients in the three groups. Also, all eye movement variables under the three paradigms had no significant correlation with clinical scale scores. CONCLUSION:Patients with major depression, bipolar depression and bipolar mania share similar eye movement dysfunction under free-viewing, fixation stability and smooth pursuit tasks.

Background and hypothesis:No objective tests are currently available to help diagnosis of major psychiatric disorders. This study evaluates the potential of eye movement behavior patterns to predict schizophrenia subjects compared to those with major affective disorders and control groups. Study design:Eye movements were recorded from a training set of UK subjects with schizophrenia (SCZ; n = 120), bipolar affective disorder (BPAD; n = 141), major depressive disorder (MDD; n = 136), and healthy controls (CON; n = 142), and from a hold-out set of 133 individuals with proportional group sizes. A German cohort of SCZ (n = 60) and a Scottish cohort of CON subjects (n = 184) acted as a second semi-independent test set. All patients met DSMIV and ICD10 criteria for SCZ, BPAD, and MDD. Data from 98 eye movement features were extracted. We employed a gradient boosted (GB) decision tree multiclass classifier to develop a predictive model. We calculated the area under the curve (AUC) as the primary performance metric. Study results:Estimates of AUC in one-versus-all comparisons were: SCZ (0.85), BPAD (0.78), MDD (0.76), and CON (0.85). Estimates on part-external validation were SCZ (0.89) and CON (0.65). In all cases, there was good specificity but only moderate sensitivity. The best individual discriminators included free viewing, fixation duration, and smooth pursuit tasks. The findings appear robust to potential confounders such as age, sex, medication, or mental state at the time of testing. Conclusions:Eye movement patterns can discriminate schizophrenia from major mood disorders and control subjects with around 80% predictive accuracy.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Here we report results from the Bipolar Exome (BipEx) collaboration analysis of whole exome sequencing of 13,933 individuals diagnosed with bipolar disorder (BD), matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in BD patients among genes under strong evolutionary constraint, a signal evident in both major BD subtypes, bipolar 1 disorder (BD1) and bipolar 2 disorder (BD2). We also find an excess of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 SCZ cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from GWAS of BD, however, are not significantly enriched for ultra-rare PTVs. Combining BD gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (ultra-rare PTVs seen in 33 cases and 13 controls, OR = 7.06, P = 2.83 x 10-9). At the protein level, AKAP-11 is known to interact with GSK3B, the hypothesized mechanism of action for lithium, one of the few treatments for BD. Overall, our results lend further support to the polygenic basis of BD and demonstrate a role for rare coding variation as a significant risk factor in BD onset.

Much has been learned about the etiology and pathogenesis of schizophrenia since the term was first used by Eugene Bleuler over a century ago to describe one of the most important forms of major mental illness to affect mankind. Both nature and nurture feature prominently in our understanding of the genesis of the overall risk of developing schizophrenia. We now have a firm grasp of the broad structure of the genetic architecture and several key environmental risk factors have been identified and delineated. However, much of the heritability of schizophrenia remains unexplained and the reported environmental risk factors do not explain all the variances not attributable to genetic risk factors. The biggest problem at present is that our understanding of the causal mechanisms involved is still in its infancy. In this review, we describe the extent and limits of our knowledge of the specific genetic/constitutional and non-genetic/environmental factors that contribute to the overall risk of schizophrenia. We suggest novel methods may be required to understand the almost certainly immensely complex multi-level causal mechanisms that contribute to the generation of the schizophrenia phenotype.

We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.